基于高阶马尔可夫链WSN低时延调度算法  

Low Delay Scheduling Algorithm Based on the High-order Markov Chain in Wireless Sensor Network

作　　者：孔凡凤 陈曦[2] 宋燕辉 欧红玉 Kong Fanfeng;Chen Xi;Song Yanhui;Ou Hongyu(Hunan Post and Telecommunication College,Changsha 410115 ,China;Changsha University of Science & Technology,Changsha 410114,China)

机构地区：[1]湖南邮电职业技术学院,长沙410115 [2]长沙理工大学,长沙410114

出　　处：《科技通报》2019年第5期90-96,共7页Bulletin of Science and Technology

基　　金：国家自然科学基金青年基金资助项目(项目编号:61502056);湖南省教育厅科学研究项目(项目编号:16C1187)

摘　　要：对于无线传感网络,节点数据到达率和服务都随着时间和环境不断变化,基于Glauber动态模型的CSMA无线传输网络的调度解决方案,吞吐量较优,但马尔可夫链对链接状态随时间推移构成根本性约束,基于此提出一种新的基于高阶马尔可夫链的低延时排队序列链路调度算法,首先观察局部链路状态信息,然后构造可行链路演化的马尔可夫链时间表。实验结果表明,通过有效的"去相关"链路进程,该方法实现吞吐量最优,而且能提供更好的延时性能。Several CSMA algorithms based on the Glauber dynamics model have been proposed for wireless sensor network link scheduling,as viable solutions to achieve the throughput optimality,yet simple to implement. However,their delay performance still remains unsatisfactory,mainly due to the nature of the underlying Markov chains that imposes a fundamental constraint on how the link state can evolve over time. In this paper,we propose a new approach toward better queuing delay performance,based on our observation that the algorithm needs not be Markov Chain,as long as it can be implemented in a distributed manner. Our approach hinges upon utilizing past state information observed by local link and then constructing a high-order Markov chain for the evolution of the feasible link schedules. We show that our proposed algorithm, named delayed CSMA, achieves the throughput optimality, and also provides much better delay performance by effectively ‘de-correlating’ the link state process. Our simulation results demonstrate that the delay under our algorithm can be reduced in some cases,compared to the standard Glauber-dynamics-based CSMA algorithm.

关 键 词：马尔可夫链 无线传感网络 低时延 载波侦听多路访问 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]